Day3

Day 3

Time	Activity	Slides	Hands-on
Morning	Metagenome assembly	Link here	Link here
Afternoon	Assembly QC		Link here

Metagenome assembly

First log in to our cloud instance with the IP provided and cd to your working directory.
Let's then pull possible changes in the Github repository:

cd physalia_metagenomics
git pull origin main

After that we're gonna go through the metagenomic assembly part, but not run the actual assembly script.
The assembly takes days and needs more resources than we have on our instance.
So the assemblies will be provided.

Short-read assembly with megahit

The short reads will be assembled using megahit.
Although, we won't be running the actual assembly, megahit is installed on our instance.

So have a look at the different options you can change in the assembly.
You can find more information about megahit from the megahit wiki.
You don't need to understand each and every option, but some of them can be important.

conda activate assembly_env
megahit -h

Questions about megahit

1. What do you think would be important? What would you change or set?
2. What version of megahit have we installed? Is it the latest?

After that have a look at the assembly script Scripts/MEGAHIT.sh.
Open it with a text editor or print it on the screen with less.

Would you have changed something else and why?

When we're satisfied with the assembly options, we would start the assembly and wait from few hours to several days depending on your data and computational resources.
But we won't do it, since we don't have to time or the resources.
Instead, you can use the assemblies and log files we have made and make soft link as before to your own folder.
We have removed some intermediate files, so the folder contains only some of the files megahit normally produces.
But the most important is the final.contigs.fa which cointains the final contigs as one might expect.

cd ~/physalia_metagenomics
ln -s ~/Share/ASSEMBLY_MEGAHIT/ ./

Inside the folder you'll find the assembly logs inside the assembly folder for each sample.
Start by looking at the assembly logs with less.

Questions about the assembly

1. Which version of megahit did we actually use for the assemblies?
2. How long did the assemblies take to finish?
3. Which sample gave the longest contig?

Long-read assembly with metaFlye

We will also assemble the Nanopore data using metaFlye (which is actually the genome assembler Flye but with different settings that are optimized for metagenomes).
You can read more about Flye/metaFlye here.

The script we are using to run metaFlye is quite simple, but let's take a look at it using less (the script is located in Scripts/METAFLYE.sh).

Again, we are not actually running the long-read assembly as this takes some time.
Instead, you will find the assemblies already made in Share/ASSEMBLY_METAFLYE.
Let's make soft link to the assembly folder as we have done before for megahit:

cd ~/physalia_metagenomics
ln -s ~/Share/ASSEMBLY_METAFLYE/ ./

Using less, look at the log files from metaFlye that are inside this folder (Sample03.metaflye.log.txt and Sample04.metaflye.log.txt) and answer the questions below.

Questions about the assembly

1. How many contigs do we have in each assembly?
2. What is the total assembly lenght of each assembly?

The downside of Nanopore (at the moment), is a somewhat higher error rate than Illumina.
But because we have sequenced the same samples using both Illumina and Nanopore, we can take advantage of the longer reads from Nanopore and the better error rates from Illumina.
We do that by correcting (polishing) the Nanopore assemblies using the short Illumina reads.
This will be done using Pilon (take a look here).

Let's take a look at the script that is located in Scripts/PILON.sh.

You will find inside the assemblies folders (ASSEMBLY_METAFLYE/Sample03 and ASSEMBLY_METAFLYE/Sample04) the output from Pilon.
The pilon.fasta file is the corrected assembly, and the pilon.changes file is a list of every single change that Pilon made to the metaFlye assemblies.
Let's take a look at the first few lines of these files using head:

head ASSEMBLY_METAFLYE/Sample03/pilon.changes
head ASSEMBLY_METAFLYE/Sample04/pilon.changes

Assembly QC

Now we have all the assemblies ready and we can use metaquast for quality control.
Activate the assembly environment if it's not already activated and run metaquast on all short- and long-read assemblies.

But first, have a look at the different options metaquast has with metaquast -h.
You should at least check the options we are using.
We will run metaquast inside a screen using the command screen. This way you can do other things or log out while metaquast is running and it won't be interrupted.

Mini manual for screen:

• screen -S NAME - open a screen and give it a session name NAME
• screen - open new screen without specifying any name
• screen -ls - list all open sessions
• ctrl + a + d - to detach from a session (from inside the screen)
• screen -r - re-attach to a detached session
• screen -rD - re-attach to a attached session
• exit - close the screen and kill all processes running inside the screen (from inside the screen)

screen -S metaquast
metaquast.py ASSEMBLY_METAFLYE/*/pilon.fasta ASSEMBLY_MEGAHIT/*/final.contigs.fa \
               -o METAQUAST_FAST \
               --threads 2 \
               --fast \
               --max-ref-number 0 &> metaquast.fast.log.txt

Detach from the screen with ctrl+a + d.
This will take ~10 min. You can re-attach with screen -r metaquast to check whther it has finished.
After it is done, we will go through the report together. Open the report file in the output folder:

less METAQUAST_FAST/report.txt

Questions about the assembly QC

1. Which assembly has the longest contig when also long reads assemblies are included?
2. Which assembly had the most contigs?
3. Were the long read assemblies different from the corresponding short read assemblies?
4. If yes, in what way?